How to Use Parseur to Extract Data from Any Email or PDF

Every day, businesses receive critical order data trapped inside emails and PDF attachments. Purchase orders arrive as styled PDFs. Shipping confirmations land as HTML emails. Supplier invoices come in every conceivable format. Manually copying this data into your systems is not just tedious; it is error-prone and unscalable. Parseur solves this by turning unstructured documents into clean, structured data that flows directly into your workflows.

This guide covers everything you need to build a production-ready Parseur setup: template creation, parsing rules, accuracy optimization, and integration with automation platforms like Make.com.

How Parseur Works Under the Hood

Parseur uses a template-based approach to data extraction. Unlike pure AI/ML document parsers that attempt to understand any document, Parseur lets you train it on specific document layouts. You highlight the data fields you want to extract, and Parseur creates rules that apply to every future document matching that template.

This template approach offers a critical advantage for business operations: predictable accuracy. Once a template is tuned, it extracts data with near-100% accuracy on documents that match the layout. The trade-off is that you need to create a new template for each distinct document format you receive.

Figure 1: End-to-end data flow from incoming email through Parseur extraction to downstream systems.

Step-by-Step Template Creation

Getting your first template right sets the foundation for everything else. Follow this process for each document type you receive:

• Step 1: Create a mailbox. Parseur gives you a unique email address (e.g., yourcompany-po@mailparser.parseur.com). Forward a sample document to this address or upload a PDF directly.
• Step 2: Highlight fields. Open the document in Parseur's visual editor and click-drag to highlight each data point you need: PO number, line items, quantities, unit prices, ship-to address, and totals. Name each field descriptively (use po_number, not field_1).
• Step 3: Set field types. Assign data types to each field: text, number, date, price, or table. Tables are critical for line items. Parseur's table extraction lets you define column headers and it will loop through every row automatically.
• Step 4: Test with variations. Forward 5-10 real documents to the mailbox and check the parsed output. Look for edge cases: missing fields, extra whitespace, date format inconsistencies, and multi-page documents.
• Step 5: Refine with conditional rules. If certain fields appear only in some documents (like a "Rush Order" flag), use Parseur's conditional parsing to handle presence/absence gracefully.

Pro tip: Name your templates after the sender or document type (e.g., "Acme Corp PO" or "Amazon Shipping Confirmation"). When you have 30+ templates, clear naming prevents confusion.

Parsing Rules That Maximize Accuracy

Templates get you 90% of the way. The remaining 10% comes from fine-tuning parsing rules for the real-world messiness of business documents.

• Anchor text. Instead of relying on position alone, anchor your field extraction to nearby static text. For example, extract the value immediately after "PO Number:" rather than "the text at coordinates (x, y)." Anchored fields survive minor layout shifts between document versions.
• Regex post-processing. Apply regular expressions to clean extracted values. Strip currency symbols from prices, normalize date formats to ISO 8601, and remove leading zeros from order numbers. This prevents downstream errors when the data hits your accounting system.
• Table row validation. For line item tables, add a validation rule that checks whether quantity and price are both numeric. Rows that fail validation (like subtotal lines or blank rows) get filtered out automatically.
• Multi-page handling. Some PDFs split a single purchase order across multiple pages. Configure your table extraction to span pages so that a 50-line-item PO is captured as one complete table, not truncated at the page break.

Integrating Parseur with Make.com

Parseur's real power emerges when you connect it to an automation platform. Make.com is the ideal partner because its iterator module handles Parseur's table output natively. Here is the standard integration pattern:

Figure 2: Make.com scenario structure for processing Parseur webhook data into downstream systems.

The Make.com scenario starts with a Parseur webhook trigger. When a document is parsed, Parseur sends the structured JSON payload to Make.com instantly. A Router module then branches the flow based on document type: purchase orders go to order creation, invoices go to accounts payable, and shipping confirmations update tracking status.

For line item data, use Make.com's Iterator module to loop through the table array. Each iteration creates a line item in your ERP or accounting system. Wrap the entire flow in an error handler that catches API failures and routes problem records to a Google Sheet for manual review.

Accuracy Optimization Strategies

Even well-built templates need ongoing tuning. Here are the strategies that separate a fragile proof of concept from a production-grade parsing pipeline:

• Version your templates. When a supplier updates their PO format, create a new template version rather than editing the existing one. This way, old documents still parse correctly if they are reprocessed.
• Monitor parse confidence. Parseur assigns a confidence score to each extraction. Route documents below 90% confidence to a human review queue instead of processing them automatically.
• Validate against master data. After extraction, cross-reference customer names and SKUs against your master database. A fuzzy match on customer name with a confidence threshold catches misspellings before they create duplicate records.
• Use dedicated inboxes per sender. Rather than one catch-all Parseur inbox, create separate inboxes for your top 10 suppliers. This ensures the correct template is always applied without relying on auto-detection.

Parseur transforms document processing from a labor-intensive bottleneck into an automated pipeline. Combined with a PDF order processing workflow, it becomes the backbone of hands-free order intake. The key is investing in template quality upfront: a well-tuned Parseur template running through Make.com can process thousands of documents per month with zero manual intervention.